Datadog at Citi’s 2025 Global TMT Conference: AI and Growth Strategies

On Wednesday, 03 September 2025, Datadog Inc. (NASDAQ:DDOG) presented its strategic outlook at Citi’s 2025 Global TMT Conference. The discussion, led by CFO David Obstler, highlighted Datadog’s rapid growth driven by AI-native companies, while also addressing potential risks such as customer concentration and churn. Obstler emphasized Datadog’s strategic initiatives in AI and cybersecurity, underscoring both opportunities and challenges in the evolving tech landscape.

Key Takeaways

• AI-native companies contributed 10% to Datadog’s growth.
• Infrastructure monitoring reached $1.25 billion in annual recurring revenue (ARR).
• The company is investing in international markets like India and Brazil.
• Datadog’s cybersecurity focus includes Cloud SIEM and app security.
• Customer insourcing is rare, reinforcing Datadog’s platform strategy.

Financial Results

• Datadog reported accelerated top-line growth in Q2, with AI-native clients playing a significant role.
• Infrastructure monitoring achieved an ARR of $1.25 billion.
• Logs and Application Performance Monitoring (APM) each recorded $750 million in ARR.
• Security solutions contributed over $100 million in ARR, while database monitoring is rapidly growing to $50 million.
• The overall ARR stands at $3.3 billion, indicating robust financial health.

Operational Updates

• Eight of the ten largest AI tool companies are Datadog customers, highlighting strong penetration in the AI sector.
• Customer acquisition strategies include winning new logos and displacing competitors.
• The small and medium-sized business (SMB) environment remains stable.
• International expansion is a priority, with investments in markets like India and Brazil.
• Datadog has 4,500 customers sending data from AI integrations, representing over 10% of its customer base.

Future Outlook

• Datadog aims to integrate new technologies to maintain a competitive edge, with a focus on AI and cloud migration.
• Key priorities include enhancing Cloud SIEM, service management, product analytics, and data monitoring.
• The company expects enterprise AI adoption to drive modernization and increased cloud workload migration.

Q&A Highlights

• AI-native customers exhibit above-average net retention, though potential for rationalization exists.
• Datadog’s guidance discounts rapid growth rates, factoring in risks like churn.
• The company is enhancing its go-to-market strategy by expanding security channels and refining sales team structures.
• Efforts to increase sales capacity focus on international markets and enterprise marketing enhancements.

In conclusion, Datadog’s strategic focus on AI and cybersecurity positions it well for future growth, despite potential challenges. For more detailed insights, readers are encouraged to refer to the full transcript.

Full transcript - Citi’s 2025 Global TMT Conference:

Unidentified speaker: At our afternoon slump off is a conversation with Datadog. Really thrilled to have David Obstler, CFO of Datadog, on stage with me. Thank you for being here.

David Obstler, CFO, Datadog: Thanks for having us. Appreciate it.

Unidentified speaker: So let’s get right into it. I wanna level set, and and kinda set the stage, with you at Mhmm. The highest level. Year to date achievements and the key milestones out of the second quarter in terms of a recap, things that I think would be worthwhile reemphasizing for all of us here?

David Obstler, CFO, Datadog: Yes, so in the second quarter, I think we accelerated our top line growth. Like a number of software vendors, we are being complemented in the investment cycle we’re going through in AI tool companies. We have and we’ve always said we have the solution that is being significantly adopted by modern software companies. And we thought that like cloud natives that would be the case with AI natives and it has been. We said on our call that we have that’s contributed 10% to our growth and that we have, I think, eight of the 10 largest AI tool companies.

We have more than a dozen over $1,000,000 We have 80 over $100,000 So in this sort of wave of software companies, we are being used for their observability. We are being used in the same ways that we’re being used by other companies, which is to monitor their production workloads. In terms of the rest of the business, it’s really a kind of a false distinction to carve out a part of software. But we’ve seen similar trends, meaning we’ve seen growth that was similar in Q2 as in the previous couple of quarters with strong winning of logos. We gave on the call a number of logos where we’ve consolidated or displaced.

So we continue to, you know, have that happen. We’ve seen a reasonably healthy SMB environment stable to reasonably healthy, which probably is reflect that’s excluding AI, which is reflective of maybe the more positive funding environment and growth dynamics in the industry. And we’ve been successful in scaling our investments both in R and D and in go to market with the go to market investments focused on expansion of our footprint, particularly in some international areas. One last thing, we have given milestones as to when we have on the product side passed certain revenue numbers. And as you recall, we’ve given milestones on infrastructure, APM, synthetics, ROM, logs, etcetera.

And this time, we gave, a milestone of crossing $100,000,000 in security, with very good growth. And at our Dash, to conclude on, the products, we made a number of product announcements. Some of the ones that were exciting included Bits AI for service management, which is in private preview right now. There was a lot of enthusiasm in helping to handle cases and resolutions more quickly, as well as some developments in data observability. We made an acquisition in product analytics and a number of things around the log business, whether it be the use in SIM or frozen logs or or denominating logs in different ways for different use cases.

So continue to advance a lot in product.

Unidentified speaker: And now we’re gonna jump on a couple of diff those different topics that you brought up. But what I do want to, you know, peel back the onion on is the AI native customers. I think you characterized this as, you know, unnecessarily a false bifurcation of a AI native versus a non AI native. And think in your defense, it’s you’re you’re damned if you do, damned if you don’t. If you don’t have AI native customers, what are you doing?

If you do have AI native customers, you know, let’s talk about the the slippery slope of navigating that concentration risk. Right? So with that in mind, maybe at the highest level, you know, clearly, it has been occupying a lot of investor mindshare. And so, you know, from that standpoint, are there any helpful perspectives you can share on the usage behavior, the consumption and usage patterns, the product portfolio Mhmm. Adoption of the AI native customers relative to the cloud natives.

And I’m framing the question this way is because we kind of saw the feast and famine, you know, hot and heavy behavior from the cloud native companies back in the COVID days. Right? So if you can kinda help us give an analog on Mhmm. You know, how these things can go from zero to 60 Yeah. 3.5, I think that would be really helpful.

David Obstler, CFO, Datadog: Yeah. It’s important. We’re a consumption model, used to monitor production environment. So we’re not paid unless there are workloads. Okay?

So the one of the, you know, big, takeaways is that a number of these companies, and you’re reading about it all the time because they’re publishing their revenues and their funding rounds, they are experiencing significant increase in workloads. So that’s the main thing that’s driving this. And we’re seeing net retention that is similar to what we saw in the highest growth of cloud natives. This is a much smaller segment than that. It’s still a relatively small percent of our revenues, but we’re growing with them because they’re being used by clients and we’re monitoring workloads.

The types of products are very similar to, our other clients in that we’re managing production environments. So it’s metrics, traces, logs, then rum and synthetics and all of that. I think it’s confusing because they are training their own models and all of that and we’re really more production environment. So we’re really the demand cycle is very similar to other high growth software companies. We are seeing a pattern where they are committing with us and then they’re growing past their commitment.

So this is no different than any other high growth company. We then use the same techniques. We have discount pricing for higher commitments and longer commitments, and so we’re doing that. And I think it’s characteristic of what the IT world is investing in because we wouldn’t be paid unless the workloads were increasing.

Unidentified speaker: And the feverish pace at which a lot of these AI native companies are driving their own businesses forward. You had made a point around net retention rates within the AI native vertical having similarities Mhmm. To the cloud native behaviors. Right? I I’m wondering, is the the baseline NRR behavior of the AI native cohort significantly above and beyond the company average?

Because that is a metric that you share? Or is it pretty much close to the pin?

David Obstler, CFO, Datadog: No. It’s above the average, and it has to be with the growth of the I mean, don’t forget, most of our revenues come from existing customers. So yes, it is above the average. This is in the growth dynamics like the cloud natives, but a much smaller percentage of the business, 10%, 11%. So it’s similar.

And then the next question is, is there going to be an optimization? Now I do think many of people in IT and development learn some things. And so it really is dependent on whether that client is managing well their cloud use and optimizing or controlling along the way. So it’s difficult for us to know that. Certainly anytime you have that type of significant growth, you could have a period of more rationalization.

It could happen, we don’t know for sure, but we’ve I think told everybody that could happen in this cohort. You

Unidentified speaker: know, down sell, churn, you know, all facets, same side of the of the coin. Right? Yeah. You know, when these large customers who are in very consistent growth experimentation mode, the optimization risk is, you know, is a fate. So when you think about some Mhmm.

Your largest AI native customers and it in and of itself, it’s a small cohort. Mhmm. How should we brace for, you know, a potential churn down sell and, you know, all the way to the other end of the spectrum? A full on insourcing intent where they say, hey. I’m just gonna I’m big enough.

I’m gonna do this in house. Mhmm. You know, how are you thinking about that level of risk to the business in in terms of the gradient of that risk?

David Obstler, CFO, Datadog: Yeah. So as everyone knows, when we give guidance, we we don’t assume these rapid growth rates. We heavily discount it. So I want to separate that out. So when we talk to you, we are discounting and risk assessing that.

But in the business itself, are full in sourcing is quite rare, okay. So there are companies that believe in it, you can see from our gross retentions that for the most part, our risk is not about full in sourcing. And we know that when we see very large tech companies and ones that whose policies are mainly do it themselves, they still use Datadog for mission critical workloads. We can’t be certain. So I think the question is, a lot of companies use a portfolio of products.

Sometimes they do things themselves, How will that evolve? Now we’re trying to work and I think we learned a lot in what happened in the cloud natives. We learned a lot about how to work with them in account management, try to advise them and get them to help themselves. That has a number of different things. If there are surges, we will tell them there’s a surge.

You’re sending us laws you shouldn’t be sending us. We’re not going to charge you for that burst, but turn it off and we help them. We even go on-site sometimes with them. And so we’ve worked on our own infrastructure with things like flex logs, frozen logs in order to look at metrics with elements, all sorts of things to try to set price in a segmented way versus the cost and not charge grossly the same SKU price for all use cases. It doesn’t cost us as much in some.

So we’re doing that in some of the product announcements and infrastructure. And we have a volume and a term based structure similar to the hyperscalers that give discounts to customers on volume. So we’ve been trying not just with the ad, but across the board to work with our clients to become a long term partner, and that’s some of the tactics we use.

Unidentified speaker: And just a little bit of a non sequitur, as you think about being proactive in your customers’ usage of the platform, ensuring they’re getting maximum ROI from, you know, more deeply using the footprint. From a sales rep and a sales organization perspective, how is a salesperson, you know, incentivized to actually tell their customer, hey. You’re actually spending too much here, or you could be better suited to utilize these capabilities at this certain rate, you know, flex logs, frozen logs. So how how are you kind of straddling those two dynamics where, fundamentally, the conversation is, hey. Use it a little less or use it more efficiently, which is right by the customer,

David Obstler, CFO, Datadog: by the So I think, one is, for a lot of these cloud natives or AI natives, they’re not covered. They’re covered by our customer success organization who is metric in a way that incentivize them to work with the client in that way. In terms of what we’re doing, we are trying the objective is to capture more of the wallet share by pricing appropriately. For instance, we know that in certain cases like Cloud SIM, the logs are not going to have to be accessed as much in real time. Sometimes there’s compliance uses, other types of uses.

So what we’re trying to do ultimately is expand our revenues with the client by capturing more use cases and not mispricing use cases that could cause the client to have uneconomic results. So our goal is to optimize this for ourselves over time in winning more and more of the wallet size and having more revenues. And that’s what’s happened in FlexLogs, where we’ve captured actually incremental use cases and also not had that type of situation with a client where they’re using logs with retrieval that’s immediate when they don’t need to do that. Those are some of what we’re doing.

Unidentified speaker: I appreciate that nuance. Zooming out, so we talked a lot about the AI native customers. What about the blue chip classic enterprise customer that you have and what that AI opportunity looks like for them? Because the, quote, unquote, core business for you has been workload migration to the cloud. Yep.

And that those are the coattails that you have been very successfully writing. Yep. Right? So what is that broader AI opportunity from the vantage point of a normal organization, a normal financial services firm that Definitely. Have

David Obstler, CFO, Datadog: Definitely. Good question. I mean, I think it’s still I think the migration is is still the anchor. And we believe because you need to modernize your stack in order to inject AI that there’s even going to be more impetus for the traditional companies. And so we think that’s the case.

So that is one way we think we’re going to monetize. Some metrics we’re looking at, for instance, we basically use integrations to get data And we have 4,500 customers out of our more than 30,000 sending us data from those AI integrations. So what they’re doing is they may have call outs to OpenAir, Anthropic, Perplexity, etcetera, and they’re sending us data. So we’re seeing signs that is starting to enter our workloads. That’s part of our platform.

But still that’s a small percentage. I mean, that’s a little over 10% of our total customers. But I think we are little by little seeing that the use of the LLM product, which is now in the many hundreds still small. And I think as we go from private preview to GA in the Bits AI service management, we’ll start to be able to report on numbers of customers using some of these things. So it’s happening, but most of it still is in internal use or training or efficiency or call outs through APIs to the models, but it’s happening.

Unidentified speaker: Staying on this topic, there has been a lot of hand wringing about the whole commodification, commoditization of the software development process, the software development life cycle, I e, if I can have 90% of code generated by an LLM, am I hiring as many people? And so the train of logic here is as follows. You know, what is the strength, the weakness, the opportunity, and threat for someone like a Datadog where maybe an organization is hiring fewer site reliability engineers or cloud engineers? So where do you fall in that paradigm?

David Obstler, CFO, Datadog: That’s a really good question. I think when you’re talking about having an enterprise grade solution, mission critical, that has to aggregate data from everywhere, organize it, and then in real time be 100% reliable for your mission critical applications. We believe that agentic function is going to be our friend. It’s going to help the platform be more valuable. And it’s going to accelerate software creation and therefore the modernization, have more of it flow through our observability.

I mean, we’re not a consumer company. It’s not like, okay, fine, if it works, it doesn’t. This has to be for security, reliability, privacy, everything. And the bar to have that handled completely agentically is very, very high. Can’t say never, but certainly way out in time.

So we think it’s going to be our friend to both enable our platform and accelerate the complexity of workloads, which will help us.

Unidentified speaker: David, you and I have talked about this offline in the past, but the secular trend around cloud migration, the the effects of IT Yeah. And architectural modernization, you know, those have been, you know Mhmm. Fine friends to your business.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Do you think the AIification of the enterprise enterprise business processes, do you think that adds to the estate growth opportunity in the cloud? So is that more volume for you to capture, or does that accelerate the pace? So there’s a volume argument, and then there is a time argument. What is your perspective on that?

David Obstler, CFO, Datadog: Yeah. Well, I think we’re there there may be some short term disruption. There may be, like, figuring it all out might cause the investment cycle to be more distributed between sort of the research projects and the training projects. But long term, I think that it’s going to result in more what drives us more market share from legacy applications, especially mission critical to modernize applications delivered in the cloud and enhance both our workloads, the size of our workloads and the complexity of the workloads and therefore give us more opportunities to monetize those workloads. We don’t know the timeframe, but if you look at what happened in containers and service list, it rings a lot of the same bells as what happened there.

And what the art of the possible is, is exciting for us If we both monitor anything that comes along, so we have to make sure we’re keeping up and we’re putting that into our platform, so that nobody can come along and say, I invented a better mousetrap because the mousetrap is right there in our platform. That’s our strategy.

Unidentified speaker: I appreciate that. David, in your opening remarks, you talked a little bit about the higher level product and platform level milestone. So infrastructure monitoring, which is your core DNA. It’s it’s your your Yeah. Stalwart franchise, 1,250,000,000.00 ARR.

You’ve got each of logs and APM running at a $750,000,000 ARR rate. You’re now a three and change, 3.3 to be exact, if I just gross up your You’re over 3,300,000,000.0 in ARR is my math. Your math. You have 2.75 spoken for.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: So can you talk to us about, you know, that pocket of 500 to 600,000,000 of ARR? What’s in that bucket? You called out security.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: So help us understand in terms of chunkiness of size in that 500 to $600,000,000 bucket. And then the related natural follow-up to that is, what do you think is going to be the star performer from a security perspective in that bucket?

David Obstler, CFO, Datadog: So we’ve already had some progress. When talking about progress, this has gotten like, say, over $100,000,000 We’ve had that with now with RUM, Synthetics, Security. We’ve had products like database monitoring, which continue to go very rapidly grow to 50,000,000. And so we’ve had we’ve given metrics to everyone on what filling up that bucket. I think some of the things that are right at the top of the priority list for us are Cloud SIEM.

There are a number of factors. First of all, we’ve really done well in the log business for cloud workloads, observability logs, you just talked about how big it is. So we have a lot of the logs. We have worked on the SIEM product and we’ve, I think done the things in logs to and the platform itself to make it appropriate for a SIEM. We have a situation where at best, Splunk’s been acquired and has priced in a way that and you look at Cribble and others where it may not be the optimal thing I talked about slicing and dicing.

So at sort of the minimum, we’re going into the cloud workloads there and saying we can offer a better product, more appropriately priced. We’re developing security channels and more specialized, I wouldn’t say we have an overlay, but we’re experimenting with expertise. And so I think that is an area where we’ve had programs, we’re getting success with big corporate names that would indicate that is so I think that’s an exciting one. The AgenTex side of things, we’re not quite sure how, but basically in service management, we see and I think we gave a very impressive demo at Dash in the power of this. So we think the combination of all of this with service management, on call, agentic, case management and remediation is a significant opportunity and one that we’ve begun to have success versus some of the incumbents like PagerDuty, Opsgenie, etcetera.

Then we’ve invested in a couple of areas where we had sort of development, but we’ve accelerated that. One is product analytics, which is feature flag and experimentation. There’s a lot of synergies with RUM. And there are a number of point solutions out there. And our approach is going to be to tightly integrate we did the Appo acquisition, tightly integrate that and do what we’ve been really good at, which is attaching that to our most proximate use cases.

So we’re excited about that. And then we have we made an acquisition in data monitoring and we’re excited about the opportunity there as well. So we think that we’re germinating a lot of different seeds that can be part of that graduating class. And why it’s important is, it’s not just that we reach that milestone, but that we increase the functionality of the platform. So we capture more and more of the usage and the attention and the wallet eventually.

So that’s what’s going on in the R and D organization.

Unidentified speaker: David, I’m going to ask you the same question, but I’m flip So it infrastructure monitoring at 1.25 it’s the the nucleus of everything that you do. Right? So on the one hand, you know, you’ve got all these adjacent skews that are just blowing the doors off in terms of growth and hitting, you know, you know, escape velocity. But that begs the question, hey. What’s happening on the infrastructure monitoring side where, you know, growth is maybe on a relative basis plateauing.

Right? Now it’s hard for me to conceive that there is saturation when, you know, between the hyperscalers, there’s

David Obstler, CFO, Datadog: Mhmm.

Unidentified speaker: Half a trillion dollars worth of spend happening. Right? So it seems a little bit silly to say, hey. That’s there’s saturation. But maybe to ask it simply, why isn’t infrastructure monitoring growing faster?

David Obstler, CFO, Datadog: Mhmm. Yeah. I think it’s basically indexed against basic workloads. And I think we’ve always said that our growth rate as a company is going to be higher because our clients are basically offered the platform. And they essentially buy $2,000,000 of commits and they use it the way they see fit.

So it’s always been a bit of a false delineation. I think that’s the one that is at the anchor, you have to have that in order to get the other things. And I think that’s something to watch. I think that is sort of moving probably because most of our business, even though we have higher growth with GCP and Azure, that’s probably moving with the non AI part of Azure as a bedrock. And, you know, we’ll we’ll have to see.

I don’t think we have a saturation. I think it’s going to move with actual workloads. So that’s a metric that involves the workload movement.

Unidentified speaker: On the cybersecurity side, and I think you’ve been awfully candid about this that, hey. This has been a work in progress from both a go to market perspective, but also, hey. There has been some white space in using capabilities. Yeah. Can you give us a rundown on where you are in the cybersecurity scope of capabilities?

How confident are you that what you have today in the market is Mhmm. Pretty competitive? And, you know, what are you doing on the go to market side to really galvanize more momentum on cybersecurity solution Good

David Obstler, CFO, Datadog: question. So I think the three main areas there is SIEM, which is more sort of compliance oriented. There is cloud security, Palo, Wizz, etcetera, and of Scott’s Squares of vulnerability and app security. And I think we are farther along on the two barbells on them in SAM, which I mentioned, where I think we have product parity. I think with integrating that in, I think we could potentially do what we did in logs.

I think we have a good app security product. I would say the sort of market size or TAM for app security has just not been as high as cloud security and SIEM. And I think we’re still in development on cloud security. Part of that is, I think, credit to some of the competitors who took some same lessons that we did in observability, which is how do you create a product that’s really easy to use, can be ubiquitous, can get the data really strong time to value and grow. And there’s been some strong competition.

I think there’s some things that we can do that maybe those competition can’t do. But I don’t think we’re in as strong in that we can handle some use cases, the ones that are DevSecOps and are aligned, but we probably don’t have a product at this point that is as fully function as it will be one day to the centralized CISO. So that’s in the product side, SIM first, AppSec, cloud security. Then when you have the go to market, as I think we’ve talked about, dev products tend to be more bought more bottoms up. They tend to be bought and experimented with hands on keyboard, where security, it’s highly governed and highly controlled by a gatekeeper, the CISO.

And that CISO has relationships, buys through channels, and is more of a top down enterprise selling. And we certainly have come we’re getting there, but we’ve come from the bottom. So I think there’s a number of things that we’re doing there that working process. We have the channel relationships. We’re trying to get to the point where we can sell security separately, not even so we can go channel with security and direct with the observability.

We have expertise in sales engineering and product and we’re experimenting now. We do have within our sales team security experts who sell the whole product, but we’re experimenting with a little bit of overlay. I think our market it’s in some ways, you’re a prisoner to your success. We’re the observability company. So how do you go about branding and creating marketing and security?

It’s something that it’s great. We’re the observability company, but and I think we’re investing more in sort of marketing dollars. So I think we’re doing a number of things and have a path and we’ll see the realization first of it as I mentioned in the cloud SIM.

Unidentified speaker: Good segue into my next question to you about, okay, there’s an abundance of opportunity in terms of the broader tailwinds and secular dynamics. But you have actively and have had more of an active reinvestment posture this year. So I’d like to take some time to discuss with you sort of where the priority sequence of those investments have been. And then even maybe taking a step back, we we talked about the numerous product pillars, if you will. And again, I know you don’t necessarily run the business that way, but I’d imagine those product pillars and those SKUs have very different gross margin profiles.

Right? So how does that ultimately filter through the p and l, and how do you adjudicate the OpEx envelope against those opportunities and kind of the bigger picture mandates around increasing sales capacity, increasing international presence, etcetera?

David Obstler, CFO, Datadog: Well, first of all, I think that they don’t have very different gross margin. It’s because of our discipline in pricing on a gross margin basis. It couldn’t have been the case that they had dramatically different gross margins or else our gross margins would have been changing, but our gross margins have been relatively stable. And I think that has to do with the pricing philosophy. And also the investment in the architecture to work on the efficiency of the architecture.

They do have direct costs in developers and in product management. We are we can be very efficient because we’re amortizing it off of a shared platform cost. So that’s why we’re more efficient in creating products than a point solution company. We’ve been trying to maintain our R and D at approximately 30% of revenues. We’ve given that target.

Sometimes it might float or but so we basically look at the priorities and we try to fit the envelope. And we are well aware that eventually we may have some coding tools, etcetera, that may create some efficiency. What we’re trying to do now is to accelerate the throughput given the pipeline, but one day we may be able to deliver a productivity story. So I think that’s been the bedrock of the company. It’s worked really well.

And then on the go to market, I think we maybe haven’t been as good, we haven’t been as consistent. And some of that has to do with I think that we took a little pause. We were a little more conservative on the back end of the bubble. And I think we didn’t grow our quota capacity as quickly as the opportunity merits, particularly in international markets. So I think there’s a number of markets where there’s white space, there’s target.

And that I mean, we didn’t have anybody in India, we didn’t have any in Brazil, and now we have teams of 50 to 100 and we’re scoring. We’re really getting great business. And so I think that’s something we’re working on. We’re also, I think, working on slicing and dicing the sales team. We have a pretty large mid market group now, and they’re getting what I would call enterprise, but they’re just the other tail end.

So I think we’re actually slicing and dicing the sales team and getting better. So that combination is the go to market investment. That’s governed by a lot of metrics, including productivity, CAC return, sales and marketing as a percentage of revenue that’s highly governed and we’re trying to lean into it assuming we get the return from it.

Unidentified speaker: You’re naturally at the stage of the company where you are doing larger transactions with larger customers, you know, with

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: More consequentiality. Right? How does that change the ethos of the go to market organization where I think historically, we’ve talked about most of your million dollar, $2,000,000 customers were graduates of Right. You know, the 100,000 ARR program. I remember we’re talking to Ali where, you know, you we’re doing, you know, victory laps with a six k PO that just boils into a 100 k.

So how has the spirit of the go to market organization changed as you naturally are going to be landing bigger and you naturally are going to be expanding much bigger?

David Obstler, CFO, Datadog: Yes. We still have that motion, but we have evolved it to and we are landing big consolidations. We have key account groups. We changed commission plans to make them more long term. We shifted our marketing dollars to more of enterprise marketing.

Unidentified speaker: And is that has that been a 2025 mandate? Or has that been a

David Obstler, CFO, Datadog: That’s been a 2025 mandate, and we’ve been working on that. We piloted that last year and continue in 2025. I think we have more, enterprise type marketing, and I think we are enhancing our channel partnerships to try to get influencers or implementers to be in the field more. And we’re also doing things like buyout credits. We’ve been doing it for some time, meaning we know it pays off and we govern this based on gross margin, but we’ll do migration credits to get them to consolidate everything on Datadog.

The return is very strong and sort of, I think probably we left some things on the table earlier by not doing that.

Unidentified speaker: My last question for you, I know we’re out of time, but the single most palpable investor misconception or misperception on the state of the business?

David Obstler, CFO, Datadog: Well, the obsession is this with this large company, which we said the

Unidentified speaker: Which

David Obstler, CFO, Datadog: named us. But we basically said that essentially, we’re a company that has been very successful in selling a platform and the vast, vast majority, 99.999 of our customers are not looking to build themselves. We also have lots of customers who are multiple millions who are doing it thus. So yes, I mean, this might be important for a very, very short term. But the more important thing here is that we’re attaching to AI workloads.

And if you believe that, it’s a great seat to be in. So I think there’s been an obsession with something that has a short term influence, but maybe isn’t part of the investment story long term in terms of maybe they’re a great customer forever, maybe they do some insourcing and outsourcing, maybe they don’t. But I think that’s probably the, call it, obsession out there.

Unidentified speaker: I like it. Okay? It’s a good place to

David Obstler, CFO, Datadog: Thank you so much.

Unidentified speaker: Always a good conversation.

David Obstler, CFO, Datadog: Good conversation. Thank you.

This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.